001467996 000__ 03939cam\\22005777a\4500
001467996 001__ 1467996
001467996 003__ OCoLC
001467996 005__ 20230707003349.0
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001467996 007__ cr\un\nnnunnun
001467996 008__ 230519s2023\\\\si\a\\\\ob\\\\001\0\eng\d
001467996 020__ $$a9789811920080$$q(electronic bk.)
001467996 020__ $$a9811920087$$q(electronic bk.)
001467996 020__ $$z9811920079
001467996 020__ $$z9789811920073
001467996 0247_ $$a10.1007/978-981-19-2008-0$$2doi
001467996 035__ $$aSP(OCoLC)1379265692
001467996 040__ $$aYDX$$beng$$cYDX$$dGW5XE$$dEBLCP
001467996 049__ $$aISEA
001467996 050_4 $$aHG176.7
001467996 08204 $$a658.15$$223/eng/20230524
001467996 1001_ $$aSen, Rituparna,$$eauthor.
001467996 24510 $$aComputational finance with R /$$cRituparna Sen, Sourish Das.
001467996 260__ $$aSingapore :$$bSpringer,$$c2023.
001467996 300__ $$a1 online resource (xiii, 353 pages) :$$billustrations (black and white, and colour).
001467996 4901_ $$aIndian Statistical Institute series ;$$v2523-3122
001467996 504__ $$aIncludes bibliographical references (pages 349-351) and index.
001467996 5050_ $$aPart I. Numerical Methods -- 1. Preliminaries -- 2. Solving a System of Linear Equations -- 3. Solving Non-Linear Equations -- 4. Numerical Integration -- 5. Numerical Differentiation -- 6. Numerical Methods for PDE -- 7. Optimization -- Part II. Simulation Methods -- 8. Monte-Carlo Methods -- 9. Lattice Models -- 10. Simulating Brownian Motion -- 11. Variance Reduction -- 12. Bayesian Computation with Stan -- 13. Resampling -- Part III. Statistical Methods -- 14. Descriptive Methods -- 15. Inferential Statistics -- 16. Statistical Risk Analysis -- 17. Multivariate Analysis -- 18. Univariate Time Series -- 19. Multivariate Time Series -- 20. High Frequency Data -- 21. Supervised Learning -- 22. Unsupervised Learning -- Appendix -- A. Basics of Mathematical Finance -- B. Introduction to R -- C. Extreme Value Theory in Finance -- Bibliography. .
001467996 506__ $$aAccess limited to authorized users.
001467996 520__ $$aThis book prepares students to execute the quantitative and computational needs of the finance industry. The quantitative methods are explained in detail with examples from real financial problems like option pricing, risk management, portfolio selection, etc. Codes are provided in R programming language to execute the methods. Tables and figures, often with real data, illustrate the codes. References to related work are intended to aid the reader to pursue areas of specific interest in further detail. The comprehensive background with economic, statistical, mathematical, and computational theory strengthens the understanding. The coverage is broad, and linkages between different sections are explained. The primary audience is graduate students, while it should also be accessible to advanced undergraduates. Practitioners working in the finance industry will also benefit.
001467996 588__ $$aDescription based on print version record.
001467996 650_0 $$aFinancial engineering.
001467996 650_0 $$aR (Computer program language)
001467996 655_0 $$aElectronic books.
001467996 7001_ $$aDas, Sourish,$$eauthor.
001467996 77608 $$iPrint version: $$z9811920079$$z9789811920073$$w(OCoLC)1304817113
001467996 830_0 $$aIndian Statistical Institute series.$$x2523-3122
001467996 852__ $$bebk
001467996 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-2008-0$$zOnline Access$$91397441.1
001467996 909CO $$ooai:library.usi.edu:1467996$$pGLOBAL_SET
001467996 980__ $$aBIB
001467996 980__ $$aEBOOK
001467996 982__ $$aEbook
001467996 983__ $$aOnline
001467996 994__ $$a92$$bISE